Multi-Variant Accuracy Evaluation of UAV Imaging Surveys: A Case Study on Investment Area.

Grzegorz Gabara,Piotr Sawicki

doi:10.3390/s19235229

Abstract

The main focus of the presented study is a multi-variant accuracy assessment of a photogrammetric 2D and 3D data collection, whose accuracy meets the appropriate technical requirements, based on the block of 858 digital images (4.6 cm ground sample distance) acquired by Trimble® UX5 unmanned aircraft system equipped with Sony NEX-5T compact system camera. All 1418 well-defined ground control and check points were a posteriori measured applying Global Navigation Satellite Systems (GNSS) using the real-time network method. High accuracy of photogrammetric products was obtained by the computations performed according to the proposed methodology, which assumes multi-variant images processing and extended error analysis. The detection of blurred images was preprocessed applying Laplacian operator and Fourier transform implemented in Python using the Open Source Computer Vision library. The data collection was performed in Pix4Dmapper suite supported by additional software: in the bundle block adjustment (results verified using RealityCapure and PhotoScan applications), on the digital surface model (CloudCompare), and georeferenced orthomosaic in GeoTIFF format (AutoCAD Civil 3D). The study proved the high accuracy and significant statistical reliability of unmanned aerial vehicle (UAV) imaging 2D and 3D surveys. The accuracy fulfills Polish and US technical requirements of planimetric and vertical accuracy (root mean square error less than or equal to 0.10 m and 0.05 m).

Highlights

Due to significant advances in the research field of digital photogrammetry, computer vision, and unmanned aerial vehicles/unmanned aerial systems/remotely piloted aircraft systems (UAVs/UASs/RPASs) [1,2] construction, there has been an important change in geoinformation acquisition and the workflow of photogrammetric data collection [3]
According to the authors’ knowledge, the complex accuracy assessment of the computing pipeline of particular photogrammetric products which we present in this paper, do not exist at present
The use of unmanned aerial vehicles (UAV) for image-based surveys is becoming increasingly widespread across the geosciences and in industries such as engineering and surveying

Summary

Introduction

Due to significant advances in the research field of digital photogrammetry, computer vision, and unmanned aerial vehicles/unmanned aerial systems/remotely piloted aircraft systems (UAVs/UASs/RPASs) [1,2] construction, there has been an important change in geoinformation acquisition and the workflow of photogrammetric data collection [3]. This has been achieved by essential developments in the UASs components [4], in sensors production [5], and in the image-based surface reconstruction, e.g., structure-from-motion (SfM) [6,7], multi-view stereo (MVS) pipeline [8]. The research and development mainly concerns, among other areas: small UAS [22], low-cost hardware solution [23], onboard sensors integration [24], Sensors 2019, 19, 5229; doi:10.3390/s19235229 www.mdpi.com/journal/sensors

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